A moment estimation–based method for the path planning of manipulators with kinematic system reliability constraints. (January 2019)

• Record Type: Journal Article
• Authors: Wang, Jin; Wang, Wei; Fu, Jianhui; Lu, Guodong
• Is Part Of: Advances in mechanical engineering. Volume 11:Number 1(2019)
• Publication Date: 2019-01
• Subjects: Path planning -- first four moments -- maximum entropy principle -- parameter sensitivity -- direct linearization method; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814018816894
• Languages: English
• ISSNs: 1687-8132

Abstract

Since the path planning plays a significant role in the manipulator's control, the system reliability evaluation and optimization for path planning are studied with consideration of the joint clearance. A simple moment estimation–based method is proposed; a linear performance function is first established using the extreme value distribution theory. Based on the maximum entropy principle, the first four moments of variables are utilized to derive a best-fit probability density function to feature the characteristics of the system distribution rather than an empirical assumption of the normality. To meet the system reliability criterion constraints, a sensitivity analysis is conducted using the direct linearization method. With modification in the tolerance of sensitive parameters, the reliability can be improved efficiently. Traditional methods, such as the first-order second moment method, the first-order reliability method, and Monte Carlo simulation, are popular in this research field and therefore they are applied as benchmark methods for comprehensive comparisons in the accuracy and efficiency. A typical serial manipulator is applied as an example to validate the feasibility of our proposed method.